Systematic review of cnidarian microbiomes reveals insights into the structure, specificity, and fidelity of marine associations.

Microorganisms play essential roles in the health and resilience of cnidarians. Understanding the factors influencing cnidarian microbiomes requires cross study comparisons, yet the plethora of protocols used hampers dataset integration. We unify 16S rRNA gene sequences from cnidarian microbiome studies under a single analysis pipeline. We reprocess 12,010 cnidarian microbiome samples from 186 studies, alongside 3,388 poriferan, 370 seawater samples, and 245 cultured Symbiodiniaceae, unifying ~6.5 billion sequence reads. Samples are partitioned by hypervariable region and sequencing platform to reduce sequencing variability. This systematic review uncovers an incredible diversity of 86 archaeal and bacterial phyla associated with Cnidaria, and highlights key bacteria hosted across host sub-phylum, depth, and microhabitat. Shallow (< 30 m) water Alcyonacea and Actinaria are characterized by highly shared and relatively abundant microbial communities, unlike Scleractinia and most deeper cnidarians. Utilizing the V4 region, we find that cnidarian microbial composition, richness, diversity, and structure are primarily influenced by host phylogeny, sampling depth, and ocean body, followed by microhabitat and sampling date. We identify host and geographical generalist and specific Endozoicomonas clades within Cnidaria and Porifera. This systematic review forms a framework for understanding factors governing cnidarian microbiomes and creates a baseline for assessing stress associated dysbiosis.

Coculture of Two Developmental Stages of a Marine-Derived Aspergillus alliaceus Results in the Production of the Cytotoxic Bianthrone Allianthrone A.

The genetically encoded, small-molecule chemical diversity of filamentous fungi is still largely unexplored and represents an attractive source for the discovery of new compounds. Here we report the production of new chlorinated bianthrones from coculture of two different developmental stages, or morphs, of a marine alga-derived Aspergillus alliaceus (teleomorph: Petromyces alliaceus) strain. The vegetative stage (asexual morph) can be separated from the morph that switched to sexual development (sclerotial morph); both produce distinct secondary metabolite patterns. Ochratoxin (1) was mainly found in the monoculture of the sclerotial morph, while the anthraquinone pigment nalgiovensin (2) was produced by the asexual morph. Surprisingly, combining cultures from both developmental stages in a coculture experiment changed the metabolite profile drastically. The chlorinated congener nalgiolaxin (3) was abundant, and newly produced bianthrones were found. Allianthrone A (4) and its two diastereomers [allianthrones B (5) and C (6)] were isolated, and the new structures were determined by extensive NMR spectroscopic analysis, supported by optical properties and X-ray crystallography. All metabolites were tested in antibiotic and cytotoxicity assays, and allianthrone A (4) showed weak cytotoxic activity against the HCT-116 colon cancer and SK-Mel-5 melanoma cell lines.

Meta-analysis of linkage studies for complex diseases: an overview of methods and a simulation study.

Linkage genome scans for complex diseases have low power with the usual sample sizes, and hence meta-analysis of several scans for the same disease might be a promising approach. Appropriate data are now becoming accessible. Here we give an overview of the available statistical methods and current applications. In a simulation study, we compare the power of different methods to combine multipoint linkage scores, namely Fisher's p-value combination, the truncated product method, the Genome Search Meta-Analysis (GSMA) method and our weighting methods. In particular, we investigate the effects of heterogeneity introduced by different genetic marker sets and sample sizes between genome scans. The weighting methods explicitly take those differences into account and have more power in the simulated scenarios than the other methods.

Single nucleotide polymorphism screening and association analysis--exclusion of integrin beta 7 and vitamin D receptor (chromosome 12q) as candidate genes for asthma.

BACKGROUND: The human genes coding for integrin beta 7 (ITGB7) and vitamin D receptor (VDR) are two of the several candidate genes for asthma and related phenotypes found in a promising candidate region on chromosome 12q that has been identified in multiple genomewide screens and candidate gene approaches. METHODS: All exons, including parts of the neighbouring introns, and the predicted promoter region of the ITGB7 gene were screened for common polymorphisms in 32 independent asthmatic and healthy probands, resulting in the detection of two single nucleotide polymorphisms (SNPs) unknown so far. In addition to these SNPs, five already described SNPs of the ITGB7 and one in the human VDR gene were analysed in a Caucasian sib pair study of 176 families with at least two affected children, using matrix assisted laser desorption/ionization time of flight mass spectrometry. All confirmed SNPs were tested for linkage/association with asthma and related traits (total serum IgE level, eosinophil cell count and slope of the dose-response curve after bronchial challenge). RESULTS: Two new variations in the ITGB7 gene were identified. The coding SNP in exon 4 causes a substitution of the amino acid GLU by VAL, whereas the other variation is non-coding (intron 3). None of the eight analysed SNPs, of either the ITGB7 or the VDR genes, showed significant linkage/association with asthma or related phenotypes in the family study. CONCLUSIONS: These findings indicate that neither the human ITGB7 nor the VDR gene seem to be associated with the pathogenesis of asthma or the expression of related allergic phenotypes such as eosinophilia and changes in total IgE level.

Fine mapping and single nucleotide polymorphism association results of candidate genes for asthma and related phenotypes.

Several genome-wide screens for asthma and related phenotypes have been published to date but data on fine-mapping are scarce. For higher resolution we performed a fine-mapping study with 2 cM average spacing in often discussed asthma candidate regions (2p, 5q, 6p, 7p, 9q, 11p, and 12q) to narrow down the regions of interest. All participants of a Caucasian family study (97 families with at least two affected sib pairs) were genotyped for 49 supplementary polymorphic dinucleotide markers. Our results indicate increased evidence for linkage on chromosome 6p, 9q, and 12q. These candidate regions were further analyzed with SNP polymorphisms in the endothelin 1 (EDN1), lymphotoxin alpha (LTA), and neuronal nitric oxide synthase (NOS1) genes. In addition, IL4 -590C>T and IL10 -592C>A, localized on chromosomes 5q and 1q, respectively, have been analyzed for SNP association. Of the six SNPs tested, four revealed weak association with the examined phenotypes. These are the IL10 -592C>A SNP in the interleukin 10 gene (p=0.036 for eosinophil cell counts), the 4124T>C SNP in EDN1 (p=0.044 for asthma), the 3391C>T SNP in NOS1 with eosinophil cell counts (p=0.0086), and the 5266C>T polymorphism, also in the NOS1 gene, for high IgE levels (p=0.022). In summary, fine mapping data enable us to confine asthma candidate regions, while variants of EDN1 and NOS1, or nearby genes, may play an important role in this context.

Weighting schemes in pooled linkage analysis.

To identify susceptibility gene regions for complex diseases a combined linkage analysis of several genome scans might give additional insights to individual studies. In this article we consider different weighting schemes to combine the score statistics of individual studies to an overall statistic within multipoint nonparametric linkage analysis by GENEHUNTER/ALLEGRO. With the Genetic Analysis Workshop (GAW) 12 asthma data sets the weights are dominated by the large differences in the relevant sample sizes.

Incorporating larger families in identity-by-descent based linkage analysis.

Genome scans for alcoholism susceptibility genes were carried out using identity-by-descent-based statistics for qualitative traits. We compared the results when 1) multipoint information was used for all families, where some had to be truncated, 2) multipoint information was used only for small families while large (untruncated) pedigrees were analyzed with a single-point approach, and 3) single-point analysis was used for all pedigrees. Differences between the methods were observed, but neither method could identify regions related to the susceptibility for alcoholism.

Analysis of principal component based quantitative phenotypes for alcoholism.

Principal component analysis was used to construct quantitative phenotypes for alcoholism. These were analyzed for linkage to genomic regions with a variance components approach. The four phenotypes considered were a factor describing medical symptoms of alcohol dependency, a factor describing a psychological profile correlated with susceptibility to alcoholism, monoamine oxidase B (MAOB) activity and an average measurement of the P3 component of event-related potentials (ERP) at the Fp electrode placements. One region (around marker GATA123C09 on chromosome 3) with suggestive evidence for linkage was detected for the P3 (Fp) measurement. For three of the four distinct phenotypes, modest evidence for linkage to a similar region (around marker ADH3 on chromosome 4) was found.

Systematic search for susceptibility genes in different populations.

We analyzed the first replicate of each of the four simulated population samples from three distinct populations by linkage and association genome scans and could identify three regions with susceptibility loci for the disease: on chromosome 1, marker D1G024, with strong evidence for gene x environment interaction; or chromosome 3, around marker D3G045; and on chromosome 5, markers D5G035-D5G042. Our results were obtained without knowing the true disease model and are compared with this model in the discussion.